During the previous three cycles of the program project which this application is seeking to renew, we have consolidated strong links with the projects which have led to several publications. As part of the renewal of the program project, we will continue to collaborate with investigators of projects in the program for (i) the design of studies using specimens collected as part of ongoing cohort studies and new trials proposed in the application, (ii) the analysis of data, and (iii) the development of data analytical methods relevant to the scientific aims of the research projects. The design and analysis of the experiments and studies to be conducted under the auspices of the program project will benefit by the inclusion of expertise in biostatistics and epidemiology. The specific aims of the Biostatistics/Epidemiology Core (BEC) are: 1) To establish methods that promote adherence to standard protocols with particular attention to data collection and management; 2) To collaborate with investigators in the projects of the program for the purpose of designing studies and analyzing data. Data from the projects will require nesting case-control studies in the complex cohort studies and the implementation of multivariate (e.g., presence of hepatitis B virus mutations in nucleotides 1762/1764, serum concentrations of the aflatoxin-specific p53 codon 249 mutation, biomarkers for aflatoxins, alkylanilines and polycyclic aromatic hydrocarbons, and treatment arms in a clinical trial) regression methods for the analyses of longitudinal binary and continuous outcome data. Furthermore, we will use methods for the evaluation of treatments administered in clinical trials using changes of biomarkers possibly following a mixture distribution (discrete component due to biomarker being equal to zero in a subgroup and a continuous component for the complement) as the primary outcome measure; 3) To develop new statistical methods appropriate for the data generated by the projects of the proposed program. Investigators of the BEC will continue to provide direction on data management, data analysis and methodological research. We have had strong collaborations in the previous cycles of the program project and we will continue to advance the methods for data analysis to characterize how environmental exposures are associated with biomarkers that measure exposure and disease risk and whether interventions can modify such associations to reduce disease in populations.